The triglyceride-glucose (TyG) index is a surrogate marker of insulin resistance (IR). Data regarding this topic is constantly increasing, however, few and heterogeneous data are available on the relationship between this index and cardiovascular mortality risk in hypertensive populations. In this context, we aimed to explore the relationship between TyG and cardiovascular mortality in a large sample of hypertensive individuals from the URRAH cohort.

A total of 12,275 hypertensive participants without previous cardiovascular events were included in this analysis. The risk of cardiovascular mortality was evaluated by the Cox regression analysis and competing risk regression analysis.

During a median follow-up of 10.5 years, 2151 deaths occurred, of which 986 were from cardiovascular disease. A linear association between TyG and cardiovascular mortality was found, in particular for a 1-standard deviation increase in TyG there was a significantly increased risk of 33 % (p < 0.0001). Furthermore, after stratification by the optimal cut-off point (4.54 Units), participants with TyG above the cut-off had a significantly increased risk of 67 % of cardiovascular mortality when compared with those with TyG below the cut-off (p < 0.0001). These results were also confirmed after adjustment for potential confounders.

The results of this study indicate that this TyG threshold is predictive of an increased risk of cardiovascular mortality in a large sample of hypertensive individuals. This cut-off can identify individuals at higher mortality risk in already high-risk patients, with a low-cost and simple non-invasive marker.

The coronavirus disease 2019 (COVID-19) pandemic threatened public health and placed a significant burden on medical resources. The Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study collected clinical, demographic, blood cytometry, serum receptor-binding domain (RBD) antibody titers, metabolomics, targeted proteomics, nasal metagenomics, Olink, nasal viral load, autoantibody, SARS-CoV-2 antibody titers, and nasal and peripheral blood mononuclear cell (PBMC) transcriptomics data from patients hospitalized with COVID-19. The aim of this study is to select baseline biomarkers and build predictive models for 28-day in-hospital COVID-19 severity and mortality with most predictive variables while prioritizing routinely collected variables.

We analyzed 1102 hospitalized COVID-19 participants. We used the lasso and forward selection to select top predictors for severity and mortality, and built predictive models based on balanced training data. We then validated the models on testing data.

Severity was best predicted by the baseline SpO₂/FiO₂ ratio obtained from COVID-19 patients (test AUC: 0.874). Adding patient age, BMI, FGF23, IL-6, and LTA to the disease severity prediction model improves the test AUC by an additional 3%. The clinical mortality prediction model using SpO₂/FiO₂ ratio, age, and BMI resulted in a test AUC of 0.83. Adding laboratory results such as TNFRSF11B and plasma ribitol count increased the prediction model by 3.5%. The severity and mortality prediction models developed outperform the Sequential Organ Failure Assessment (SOFA) score among inpatients and perform similarly to the SOFA score among ICU patients.

This study identifies clinical data and laboratory biomarkers of COVID-19 severity and mortality using machine learning models. The study identifies SpO₂/FiO₂ ratio to be the most important predictor for both severity and mortality. Several biomarkers were identified to modestly improve the predictions. The results also provide a baseline of SARS-CoV-2 infection during the early stages of the coronavirus emergence and can serve as a baseline for future studies that inform how the genetic evolution of the coronavirus affects the host response to new variants.

Drug hypersensitivity reactions to essential antibiotics like vancomycin pose significant diagnostic and therapeutic challenges, particularly in vulnerable populations such as pediatric patients with immune deficiencies. We present the case of a 7-year-old girl with primary immunodeficiency who experienced immediate hypersensitivity reactions to vancomycin, including urticaria and angioedema, managed with corticoids and antihistamines. The Basophil Activation Test (BAT) conducted two years after the last allergic episode revealed significant basophil activation across all tested vancomycin dilutions, with CD63 and CD203c expression exceeding negative and positive controls. These findings confirm vancomycin hypersensitivity and underscore the BAT's utility as a reliable in vitro diagnostic tool, especially in settings where skin testing or specific IgE assays are unavailable. This case highlights the BAT's potential for broader adoption in clinical allergy practice, particularly in resource-limited environments. It emphasizes the importance of reliable diagnostic methods for managing drug hypersensitivity in high-risk patients.

Extracellular matrix (ECM) is a dynamic, three-dimensional network that provides structural support and regulates key biological processes, including cell adhesion, migration, differentiation, and signal transduction. Its mechanical properties, such as stiffness, topology, and viscoelasticity, are crucial in normal and pathological conditions, influencing cell behavior through mechanotransduction pathways. Dysregulation of ECM is linked to various diseases, making a thorough understanding of its composition and properties essential. This review discusses ECM composition, physical properties, and the limitations of in vitro ECM models. It highlights the role of ECM in tissue homeostasis, particularly in regulating cell behavior via mechanotransduction, focusing on force-sensitive sensors like integrins, Piezo1, TRPV4, and YAP/TAZ. Additionally, the review explores ECM remodeling in cancer, fibrosis, and cardiovascular diseases, along with current therapeutic strategies targeting ECM components, such as nanotechnology-based therapies, small molecule inhibitors, and CAF-targeted therapies. Challenges and clinical applications of these therapies are also discussed. Finally, the review looks ahead to future research, emphasizing the integration of ECM-targeted therapies in precision medicine and novel approaches to normalizing ECM composition and structure for therapeutic benefits. This review provides mechanobiological insights into therapeutic strategies targeting the ECM.

RNA interference (RNAi) is a natural biological mechanism that regulates gene expression by degrading a specific target messenger RNA, resulting in reduced production of the target protein. RNAi therapeutics can silence the production of a disease-causing protein in a specific organ or cell type and have the advantage of having a long duration of effect due to their inherently stable duplex structure and chemical modifications. Following the development of RNAi-based platform technologies, a growing number of RNAi therapeutics have now been approved across a range of diseases. Transthyretin amyloidosis (ATTR) is a progressive, debilitating, and fatal disease caused by ongoing accumulation of toxic transthyretin (TTR) amyloid deposits in multiple organs and tissues. This review describes the clinical development of patisiran and vutrisiran, which target the hepatic production of TTR for the treatment of ATTR amyloidosis. Findings from clinical studies show that rapid knockdown of TTR by RNAi therapeutics initiates a cascade of effects that ultimately leads to benefits across multiple clinical, quality of life, imaging, and biomarker disease measures of ATTR amyloidosis disease progression.

The study aims to systematically analyze the body of literature concerning the effects of colchicine on the cardiovascular system, providing a comprehensive evaluation of the current knowledge and highlighting the clinical and scientific relevance of colchicine in this field.

Data were obtained from the Web of Science (WOS), Scopus, and PubMed databases on March 17, 2025. The search terms included "Colchicine" AND ("Cardiovascular Diseases" OR "Heart Diseases" OR "Coronary Artery Disease" OR "Myocarditis" OR "Pericarditis" OR "Atherosclerosis" OR "Heart Failure" OR "Myocardial Infarction" OR "Ischemic Heart Disease" OR "Acute Coronary Syndrome" OR "Cardiac Arrhythmias" OR "Thrombosis" OR "Stroke"). No restrictions were applied regarding publication date or language, ensuring the comprehensive retrieval of relevant data. Publications were categorized according to their document type and indexes. Additionally, a cooccurrence analysis of key words was conducted using VOSviewer 1.6.18.

A total of 425 publications on the effects of colchicine on the cardiovascular system were identified, published between 1976 and 2025. There has been a significant increase in research since 2015. Most publications were in the Cardiac Cardiovascular Systems category. "Colchicine" was the most frequently used key word, appearing 170 times. The USA ranked first in publication count, with 163 studies. The USA, Italy, Canada, and China played significant roles in global research collaboration.

This bibliometric analysis demonstrates the increasing importance of colchicine as a therapeutic agent in the management of cardiovascular disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a persistent hepatic condition linked with cardiovascular disorders and metabolic disturbances. Characterized by inflammation, fat accumulation, and fibrosis within the liver, MASLD can develop into liver cancer and cirrhosis. With a global prevalence of 32.4%, the condition parallels rising obesity rates. Orlistat inhibits lipase enzymes and, therefore, reduces dietary fat absorption, which may benefit MASLD patients. The present systematic review and meta-analysis were performed in accordance with PRISMA guidelines. Searches of PubMed, Scopus, Web of Science, and Embase up to January 2025 were performed using specific keywords and MeSH terms. Bias assessment and data extraction were conducted using Joanna Briggs Institute (JBI) tools independently by two researchers. Statistical analyses were performed with Stata version 14, calculating standardized mean differences, 95% confidence intervals (CI), and heterogeneity (by performing Cochran's Q test and I² index). Moreover, meta-regression, subgroup analyses, and sensitivity analyses were conducted. Eleven studies featuring 582 participants were included. Orlistat treatment induced a significant reduction in levels of alanine transaminase (ALT) (SMD = -26.23; 95% CI = -34.70 to -17.76) and aspartate aminotransferase (AST) (SMD = -19.62; 95% CI = -28.33 to -10.92). Furthermore, reductions in HOMA-IR, body mass index, cholesterol, insulin, and waist circumference were observed. The included studies exhibited low to moderate heterogeneity for most outcomes, indicating consistent results across trials. Orlistat significantly improved AST, ALT, and some other metabolic parameters in MASLD patients, suggesting its potential as an additional treatment option. However, the outcome must be interpreted cautiously, considering study heterogeneity. Further high-quality, multicenter research is necessary to confirm these results.

Bawei Chenxiang Powder(BCP), first documented in the Tibetan medical work Four Medical Classics, has been widely applied in clinical practices in Tibetan and Mongolian medicines since its development. It has the effect of clearing the heart heat, calming the mind, and inducing resuscitation. On the basis of BCP, multiple types of formulae have been developed, such as Bawei Yiheyi Chenxiang Powder, Bawei Rang Chenxiang Powder, and Bawei Pingchuan Chenxiang Powder, which are widely used for treating cardiovascular and respiratory diseases. Current pharmacological research has revealed the pharmacological effects of BCP and its related formulae against myocardial ischemia, cerebral ischemia, renal ischemia, and anti-hypoxia. BCP and its related formulae introduced more treatment options for related clinical diseases and provided insights for fully comprehending the essence and pharmacological components of the formulae. This paper systematically reviewed the clinical and pharmacological research on BCP and its related formulae, analyzing the formulation principles and potential key flavors and active ingredients. This lays a fundamental scientific basis for the clinical use, quality evaluation, and subsequent development and application of BCP and its related formulae, providing references for studying traditional Chinese medicine formulae in a thorough and systematic manner.

Cerebral amyloid angiopathy (CAA) and insomnia are age-related neurological disorders increasingly recognized as being closely associated. However, research on the shared genes and their biological mechanisms remains limited. This study aims to identify common genes between CAA and insomnia and explore their potential molecular mechanisms, offering new insights for diagnosis and treatment. Blood samples were collected from 11 CAA patients and 11 healthy controls, followed by RNA sequencing (RNA-seq). Additionally, the microarray dataset GSE208668 for the insomnia cohort was downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis was performed to identify common differentially expressed genes (DEGs). Protein-protein interaction (PPI) networks and machine learning methods Random Forest (RF) and Extreme Gradient Boosting (XGBoost) were used to narrow down key genes. We explored the biological functions of these genes through immune cell infiltration, metabolic and Hallmark pathway analyses, and clinical correlation analysis. Co-expression networks, drug-mRNA networks, transcription factor (TF)-mRNA-miRNA networks, and competing endogenous RNA (ceRNA) networks were also constructed. Finally, hub gene expression patterns were analyzed using the Human Protein Atlas (HPA) database, and validation was performed in clinical samples and animal models using quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) and Western blot. Differential expression analysis identified 185 DEGs. PPI network construction and machine learning methods identified CBX5 and POLR1B as common hub genes for both insomnia and CAA. Immune infiltration, metabolic, and Hallmark pathway analyses revealed these hub genes play distinct roles in each disease. Various network models were constructed to explore their regulatory mechanisms. The reliability of the hub genes was validated using bioinformatics analyses and experimental approaches. This study, combining bioinformatics and experimental validation, identifies CBX5 and POLR1B as shared hub genes for CAA and insomnia. These findings offer new molecular targets for the diagnosis and treatment of both diseases, providing a foundation for future research.

While inflammation is a vital immune response to harmful stimuli, chronic inflammation has been associated with several diseases such as arthritis, cardiovascular disorders, and cancers. Plant extracts, rich in bioactive compounds, have been used in traditional medicine to manage inflammation by modulating inflammatory pathways. Specifically, Ziziphus nummularia (Sidr), known for its anti-inflammatory, antioxidant, and antimicrobial properties, contains flavonoids, saponins, triterpenoids, and phenolics, but its mechanisms of action remain unclear. This study investigated the anti-inflammatory effects of an ethanolic extract from Z. nummularia leaves (ZNE) in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages. ZNE significantly reduced the expression of pro-inflammatory enzymes (COX2, iNOS), inhibited the production of inflammatory mediators (NO, ROS, TNF-α, IL-6), reduced cellular migration and modulated key signaling pathways (NF-κB, STAT-3, MAPKs). These findings highlight the potential of ZNE as a natural therapeutic agent for inflammation, warranting further exploration of its mechanism of action and potential clinical applications.